similar to: Question concerning Box.test

Hi everyone, I've got a question concerning the function acf(.) in R for calculating the autocorrelation in my data. I have a table with daily returns of several stocks over time and I would like to calculate the autocorrelation for all the series (not only for one time series). How can I do this? After that I want to apply an autoregressive model based on the estimated lag in the

Hello everyone I have a couple of questions about the usage of the R function "read.table(.)". My point of departure is that I want to import a matrix (consisting of time and daily stock returns of many stocks) in R. Most of the data is numeric, however some values are missing (blanks) and in other cases I have the character "#DIV/0!" (from excel). My goal is to do some

Hi David, In the general case, there is still a gap in your solution >sum( tbl["1", 2:ncol(tbl)] ). This solution refers to a specific column number (here: column number 2) and not to the actual length of the run, doesn't it? That is, in this simple example the column number 2 actually corresponds to the length "2", but this must not be the case in general. For

Hello everyone, I'd like to search for certain "expressions" (characters) in my data.frame and delete the containing columns. So, for example in the below table, I'd like to delete all columns which contain the expression "Error". That is, R should delete column C and E from my data. Any ideas? A B C D E 12

Hi everyone, My (simplified) problem is the following one: I have two tables. The first table contains 5 columns with 5 values and the second table contains a single value for each vector name of the first table (see tables below): Table 1: A B C D E 1 2 3 4 5 2 3 4

Hi everyone I've got a problem regarding the arima() and the ar() function for autoregressive series. I would simply like to combine them. To better understand my question, I first show you how I'm using these two functions individually (see file in the attachement). 1) apply(TSX,2, function(x) ar(na.omit(x),method="mle")$order # this function finds the optimal

Hi everyone, I've got two data sets as below. My question now is: how can I use Dataset2 as a filter for Dataset1? My goal is just to keep the rows of Dataset1 where the first column (Date) matches the Dates in Dataset2. I would appreciate any solutions to this issue. Many thanks! S.B. Dataset1: Date A B C D 1

Hi I have probably a very simple question but I'm going crazy trying to find the solution. I have two data.frames with headers and I'm doing an intersection between them by names, such that the intersected data.frames are returned by: df1[intersect(names (df1), names(df2))] and the same for df2 Now, I want to have all the opposite data that did not intersect. I tried to do:

Hi everyone Do you know about any possibility in R to check for consecutive numbers in vectors? That is, I do not only want to count the number of observations in total (which can be done table(x)), but I also want to count for instance how many times that vector contains a certain number consecutively. For example in the following vector x the number "1" appears 7 times.

Hi everyone, I've got a question concerning missing values in R. I'm looking for an R code which removes all NA values in my data.frame. I found many answers about how to remove rows or columns which contain NA's. My problem however is a bit different. I have a list of vectors. Each vector contains some NA Values that I want to remove. So, at the end all vectors will have

Hi everyone, I have a large data set with about 3'000 columns and I would like to exclude all columns which include three or more consecutive zeros (see below example). A further issue is that it should just jump NA values if any. How can I do this? In the below example R should exclude column C and D (since in D jumping the NA leaves three consecutive zeros). I would appreciate

Dear all, propably this question sounds stupid to you, but since I'm new to R I got some troubles regarding the following issue (The table below does not represent my real data, it is just a simplified example): My intention is to first subdivide my data into several groups of vectors, let's say for instance 3 groups, such that group 1={A,B}, group2={C,D}, group3={E,F}. How can I